A dataset of 350 visual and thermal water images was created, enabling image-based temperature classification (84% accuracy) and pH classification (78%, patent pending). Machine-learning models predict potability using physicochemical and microbial data, and a prototype image-based pH software is developed. An HRD workshop on UAV-based water-quality monitoring was also conducted.
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